Lyme borreliosis in children – trends in epidemiology. A single-centre study
Bibliographic record
Abstract
Introduction The aim of the study was to assess the changing incidence of Lyme borreliosis (LB) in a children’s group in Wielkopolska, and the influences of gender and age as well as erythema migrans (EM) occurrence on the development of various forms of LB in children. Material and methods Retrospective analysis covered the medical records of 206 children diagnosed with LB, hospitalised in the Department of Infectious Diseases and Child Neurology in Poznań and consulted at its Clinic of Infectious Diseases from 1 January 2012 to 30 October 2021. For an epidemiological analysis, the study population was limited to patients from Wielkopolska. A total of 196 qualified subjects were divided into 2 time periods, the first covering the years 2012–2016, in which LB was confirmed in 52 children, and the second covering 2017–2021, in which the disease was diagnosed in 144 children. The relationship between the course of LB and the gender and age of the patients was analysed in both groups. Statistical analysis of the data was performed, and the results were compared with published data. Results The epidemiological analysis showed a more than a twofold increase in the number of LB cases in the analysed time periods, mainly diagnosed as EM. The high incidence of LB neurological complications in children, including those with incorrectly diagnosed EM, remains constant. There was no relationship between the clinical forms of the disease and the child’s sex, but an increase in the number of EM diagnoses in younger children was confirmed. Conclusions The study confirmed the increase in the number of LB diagnoses, analogous to the entire population of the region. The significant increase in the number of early stages of the disease and the frequent occurrence of neurological complications in children with undiagnosed and untreated EM indicate the need for ongoing education in the diagnosis of LB.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".